• The Journal of Korea Robotics Society
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• v.7 no.3
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• pp.171-181
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• 2012

Outdoor mobile robots are faced with various terrain types having different characteristics. To run safely and carry out the mission, mobile robot should recognize terrain types, physical and geometric characteristics and so on. It is essential to control appropriate motion for each terrain characteristics. One way to determine the terrain types is to use non-contact sensor data such as vision and laser sensor. Another way is to use contact sensor data such as slope of body, vibration and current of motor that are reaction data from the ground to the tire. In this paper, we presented experimental results on terrain classification using contact sensor data. We made a mobile robot for collecting contact sensor data and collected data from four terrains we chose for experimental terrains. Through analysis of the collecting data, we suggested a new method of terrain feature extraction considering physical characteristics and confirmed that the proposed method can classify the four terrains that we chose for experimental terrains. We can also be confirmed that terrain feature extraction method using Fast Fourier Transform (FFT) typically used in previous studies and the proposed method have similar classification performance through back propagation learning algorithm. However, both methods differ in the amount of data including terrain feature information. So we defined an index determined by the amount of terrain feature information and classification error rate. And the index can evaluate classification efficiency. We compared the results of each method through the index. The comparison showed that our method is more efficient than the existing method.

• Composites Research
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• v.24 no.6
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• pp.49-55
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• 2011

The use of advanced composite materials in main structures of military and civil aircraft has been increased rapidly because of their considerable metals in high specific strength and stiffness. However, the mechanical properties of composite materials may severely degrade in the presence of damage. Especially, the high-velocity impact such as a hailstorm, and a small piece of tire or stone during high taxing, can cause considerable damage to the structures and sub-system in spite of a very small mass. However, it is not easy to detect the damage in composite plates using a single sensor or any conventional methods. In this paper, the PVDF sensors and AE sensors were used for monitoring high-velocity impact damage initiation and propagation in composite laminates. The WT(wavelet transform) is used to decompose the sensor signals. In the PVDF sensor and AE sensor signal analysis, amounts of high-frequency signals are increased when the impact energy is increased. PVDF sensor and AE sensor signal appeared similar results. This study shows how various sensing techniques can be used to characterize high-velocity impact damage of advanced composite laminates.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.10a
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• pp.499-506
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• 2002

The purpose of this study is to develop landslide susceptibility analysis techniques using artificial neural networks and to apply the newly developed techniques for assessment of landslide susceptibility to the study area of Yongin in Korea. Landslide locations were identified in the study area from interpretation of aerial Photographs and field survey data, and a spatial database of the topography, soil type and timber cover were constructed. The landslide-related factors such as topographic slope, topographic curvature, soil texture, soil drainage, soil effective thickness, timber age, and timber diameter were extracted from the spatial database. Using those factors, landslide susceptibility and weights of each factor were analyzed by two artificial neural network methods. In the first method, the landslide susceptibility index was calculated by the back propagation method, which is a type of artificial neural network method. Then, the susceptibility map was made with a GIS program. The results of the landslide susceptibility analysis were verified using landslide location data. The verification results show satisfactory agreement between the susceptibility index and existing landslide location data. In the second method, weights of each factor were determinated. The weights, relative importance of each factor, were calculated using importance-free characteristics method of artificial neural networks.

• The Transactions of the Korea Information Processing Society
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• v.2 no.5
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• pp.677-690
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• 1995

In this paper, we propose the high efficiency data compression capable of error control using block-sorting, move to front(MTF) and arithmetic code with variable length in to fixed out. First, the substring with is parsed into length N is shifted one by one symbol. The cyclic shifted rows are sorted in lexicographical order. Second, the MTF technique is applied to get the reference of locality in the sorted substring. Then the preprocessed sequence is coded using VF(variable to fixed) arithmetic code which can be limited the error propagation in one codeword. The key point is how to split the fixed length codeword in proportion to symbol probabilities in VF arithmetic code. We develop the new VF arithmetic coding that split completely the codeword set for arbitrary source alphabet. In addition to, an extended representation for symbol probability is designed by using recursive Gray conversion. The performance of proposed method is compared with other well-known source coding methods with respect to entropy, compression ratio and coding times.

• The KIPS Transactions:PartC
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• v.10C no.7
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• pp.843-850
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• 2003

Script viruses are easy to make a variation because they can be built easily and be spread in text format. Thus signature-based method has a limitation in detecting script viruses. In a consequence, many researches suggest simple heuristic methods, but high false-positive error is always being an obstacle. In order to overcome this problem, our previous study concentrated on analyzing data flow of codes and has low-false positive error, but still could not detect a polymorphic virus because polymorphic virus loads self body and changes it before make a descendent. We suggest a heuristic detection method which expands the detection range of previous method to include polymorphic script viruses. Expanded data flow analysis heuristic has an expanded grammar to detect Polymorphic copy Propagation. Finally, we will show the experimental result for the effectiveness of suggested method.

• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.12-22
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• 2017

It is important to predict accurately reverberation level, which is a limiting factor in underwater target detection. Recently, the studies have been expanded from monostatic sonar to bistatic sonar in which source and receivers are separated. To simulate the bistatic reverberation level, the computation processes for propagation, scattering strength, and scattering cross section are different from those in monostatic case and more complex computation processes are required. Although there have been many researches for bistatic reverberation, few studies have assessed the bistatic scattering cross section which is a key factor in simulate reverberation level. In this paper, a new method to estimate the bistatic scattering cross section is suggested, which uses the area of intersection between two circles. Finally, the reverberation levels simulated with the scattering cross section estimated using the method suggested in this paper are compared with those estimated using the methods previously suggested and those measured from an acoustic measurements conducted in May 2013.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.2
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• pp.87-94
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• 2014

In solid mechanics, the peridynamics theory has provided a suitable framework for material failure and damage propagation simulation. Peridynamics is computationally expensive since it is required to solve enormous nonlocal interactions based upon integro-differential equations. Thus, multiscale coupling methods with other local models are of interest for efficient and accurate implementations of peridynamics. In this study, peridynamic models are restricted to regions where discontinuities or stress concentrations are present. In the domains characterized by smooth displacements, classical local models can be employed. We introduce a recently developed blending scheme to concurrently couple bond-based peridynamic models and the Navier equation of classical elasticity. We demonstrate numerically that the proposed blended model is suitable for point loads and static fracture, suggesting an alternative framework for cases where peridynamic models are too expensive, while classical local models are not accurate enough.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.644-651
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• 1997

In the water purification plant, chemicals are injected for quick purification of raw water. It is clear that the amount of chemicals intrinsically depends on water quality such as turbidity, temperature, pH and alkalinity. However, the process of chemical reaction to improve water quality (e.g., turbidity) by chemicals is not yet fully clarified nor quantified. The feedback signal in the process of coagulant dosage, which should be measured (through the sensor of the plant) to compute the appropriate amount of chemicals, is also not available. Most traditional methods focus on judging the conditions of purifying reaction and determine the amounts of chemicals through manual operation of field experts using Jar-test data. In this paper, a systematic control strategy is proposed to derive the optimum dosage of coagulant, PAC(Polymerized Aluminium Chloride), using Jar-test results. A neural network model is developed for coagulant dosing and purifying process by means of six input variables (turbidity, temperature, pH, alkalinity of raw water, PAC feed rate, turbidity in flocculation) and one output variable, while considering the relationships to the reaction of coagulation and flocculation. The model is utilized to derive the optimum coagulant dosage (in the sense of minimizing turbidity of water in flocculator). The ability of the proposed control scheme validated through the field test has proved to be of considerable practical value.

• Journal of the Korean Geophysical Society
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• v.3 no.4
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• pp.251-260
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• 2000

Applicabilities of two numerical methods, the 2-dimensional and the 3-dimensional method, are evaluated to inverse test results obtained from the underwater SASW(Spectral -Analysis-of-Surface-Waves) method. As a result of this study, it has been found that the 2-dimensional method can supposed to be applicable for the cases where stiffness of soil layer increases gradually with depth, and the stiffness is relatively low. For the other cases, however, it has been concluded that the 3-dimensional method needs to be applied to determine realistic theoretical dispersion curves. An example is also shown that in situ soil profile underwater is estimated from experimental dispersion curves using the 3-dimensional method. As a results, it can be concluded that the underwater SASW method can be effectively applied to explore the underwater soil condition.

• Fire Science and Engineering
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• v.34 no.3
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• pp.1-7
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• 2020

Due to the complexity and large size of buildings, plastic resin is widely used as a building material. Accordingly, the occurrence of fires caused by plastics is increasing. Due to the nature of plastic resin fires, the amount of damage to properties and human life caused by combustion products such as smoke are large, and these damages are related to smoke production and smoke generation. Therefore, this study reviews smoke measurement methods and laws on domestic buildings and fire services. Experiments were conducted based on three smoke-related test standards (ISO 5660-1, ISO 12136, ASTM E 662). The experiment results indicate a total smoke production and generation by PP, PVC, and PMMA of 43.27, 32.83, and 12.33 ㎡, and 27.855, 9.599, and 6.975 g, respectively.